In the East of England region, 80,000-125,000 hospital bed days are required to treat patients with respiratory infections each year. The most challenging patients to treat are the most vulnerable: the elderly, neonates and those suffering from chronic conditions such as cystic fibrosis (CF), Chronic Obstructive Pulmonary Disease (COPD) or HIV. Respiratory infections in patients with chronic disease conditions can be difficult to treat: infection with even the most common respiratory pathogens may prove fatal.
Many patients with CF are colonised with one or more pathogens, the most common being Pseudomonas aeruginosa. This gram-negative bacterium colonises CF patients and evades all attempts at eradication. It undergoes numerous flare-ups (exacerbations) and the inflammation it causes results in the permanent loss of lung function. It also becomes resistant to antibiotics over time, making each subsequent infection more difficult to control than the last. This is an adaptable, resilient and lethal pathogen to be colonised with. The challenge for clinicians treating CF patients is to reduce the number of infections and decrease the severity of each infection. In doing so, lung function is preserved and life expectancy is increased. For most CF patients, a lung infection with the resulting sepsis and multiple organ failure, is the primary cause of death.
Infection with P. aeruginosa becomes problematic when there is an exacerbation of infection, triggered by other factors. If not treated promptly and with the correct antimicrobial medication, the patient may be admitted to hospital for 2-4 weeks until the infection can be controlled. This exacerbation and the lung inflammation which follows can be accompanied by a dramatic and often permanent loss of lung function and the rise in exotoxins produced by the pathogen, leading to sepsis.
At every stage in the treatment of infections, CF patients must travel to their clinic and see their clinician as an outpatient for several consultations. Failure to control infection as an outpatient results in a long-stay admission. Continued failure to control the frequent infections (a CF patient may suffer 4-6 infections a year), will cause irreparable damage to health which again, increases the cost of healthcare over the life-time of the patient.
It is important to note that it is not merely the presence of an infection which is adverse to patients. Many patients will have an ongoing, low level, infection which is subject to periodic exacerbations. Predicting the timing of these exacerbations is significant for management of treatment. Simply detecting the presence or absence of bacteria—for example, by nucleic acid sequencing—will not in itself be informative as to the likelihood of an exacerbation, as exacerbations can be triggered by many factors.
It is known to use the presence of a biomarker, such as a secreted protein, as a diagnostic for infection. For example, we have previously developed a simple laboratory-based test to measure P. aeruginosa Exotoxin A (a well known marker of infection by P. aeruginosa) in the patient's sputum.
But relying on a single biomarker for accurate assessment of the status of infection is problematic. For example, products which detect other pathogens often only look for toxins, such as the many rapid tests for C. difficile that are already on the market. These detect the presence of bacterial Toxins A and B in faecal samples. While quick to perform (30 minutes), these rapid tests have low accuracy because toxins A and B may not be produced during all infections or cannot be detected in a given sample—this gives a low detection rate compared with the slower, but more sensitive methods of culturing cells from a sample by traditional microbiology (2-3 days). Furthermore, it is believed that bacterial populations may alter the profile of toxins or other proteins produced over time in response to environmental factors; within a given population, there may be only some cells which produce a particular protein while the remaining cells contribute to the infection but rely on these exogenous proteins for their survival. It is also known that a given population of bacteria in a colonised patient mutate over time from the wild type with which the host was originally infected. Accordingly, detecting a single protein may not be sufficiently accurate as a diagnostic of the likelihood of an exacerbation.
To avoid this risk of poor accuracy, we have identified in the present invention several biomarkers which can be measured quantitatively. In addition, we can also profile biomarkers that indicate the status of the host's response to this pathogen. We believe that taken together, a combination of these markers can be used to detect an exacerbation before the patient feels unwell, thereby reducing the time to prescribe the first antibiotic and therefore reducing the severity of infection.
Martin et al., Biometals (2011) 24: 1059-1067 describes the detection of siderophores produced by Pseudomonas aeruginosa in the sputum of patients with cystic fibrosis. They found an association between presence of pyoverdine and number of bacteria, but not in 21 out of 148 patients; and conclude that there is no correlation between the amount of bacteria and clinical status. The authors also conclude that the levels of siderophores do not markedly change during exacerbations. This publication therefore teaches that profiling with siderophores cannot be used to determine the level of virulence.
By contrast, as described further below, the present inventors have determined that siderophores are a useful marker for bacterial exacerbations, when used in combination with other markers. We therefore provide an accurate and rapid test for determining such exacerbations.
Jaffar-Bandjee et al., Journal of Clinical Microbiology, April 1995, p 924-929 describes the production of elastase, exotoxin A, and alkaline protease in sputa during pulmonary exacerbation of CF in patients chronically infected by Pseudomonas aeruginosa. They found that the concentrations of exoproteins varied by patient on admission (that is, after the exacerbation begins), but that the three proteins studied (elastase, Exotoxin A and alkaline protease) had similar levels. However, it is apparent from data presented in the current application that different patients may include different bacterial populations which produce different toxins or markers. Further, no test was made to detect exoprotein levels prior to exacerbations. Therefore profiling any of these exoproteins either alone or in combination will not provide sufficient data to predict all exacerbations in all CF patients.
Further, with an objective and quantitative test, the treating clinician will be able to quickly determine the performance of an antimicrobial medication in controlling the infection, substituting one antibiotic for another if the first fails to bring the infection under control. Typically, it can take up to 3 weeks to try different antibiotic combinations in an iterative process, before an effective solution is established—this is usually achieved by “informed guesswork” on the part of the expert clinician. With our diagnostic test, we believe that the time taken to perform this most necessary trial-and-error process could be reduced from 3 weeks to just 7 days.
For patients with CF, infection leads to inflammation of the lung and the greater the inflammation and time of inflammation, the greater the loss of lung function. Most CF patients suffer 4 infections each year and can spend 50% of their time in hospital. This could be reduced through the use of our new multi-marker test.
Many hospital admissions would be avoided if there was a rapid and accurate assessment of individuals with bacterial infections. One of the major difficulties when assessing patients with respiratory infections is to distinguish bacterial from viral infections. Clinical features are frequently misleading and many patients subsequently admitted to hospital had encountered delays in receiving antibiotics in the community. In the USA approx 1-in-18 or 5.51% or 15 million people per year have misdiagnosed lower respiratory tract infections.
Moreover, primary healthcare workers also face the dilemma of selecting appropriate antibiotics. While empirical antibiotic selection usually results in satisfactory treatment, the ability to identify the level of threat to a vulnerable patient posed by an identified pathogen, would permit optimised antibiotic usage. This would result in: improved early treatment success thereby preventing clinical deterioration and subsequent hospital admission, and reduced use of broad spectrum antibiotics.